During the past year we have continued enhancement of imaging platforms to guide cardiovascular catheter based treatments. These have included co-registered MRI with conventional X-ray, as well as standalone real-time MRI. Static 3D roadmaps derived from MRI datasets are used to enhance image guidance for X-ray cardiovascular interventional procedures, and indeed have been used in this lab to develop novel treatments such as mitral cerclage annuloplasty. Static roadmaps do not accurately represent cardiovascular anatomy during cardiac and respiratory motion. We have developed a system to measure respiratory and cardiac motion from real-time MRI scans and to derive a set of affine models which can be used to beat and breath the 3D roadmaps overlaid on live X-ray. We also have developed robust fully automatic mathematical techniques to register fiducial markers between imaging modalities. We will continue to improve the workflow and usability of the system so that it can be used on a routine basis to guide procedures. We have developed a system of adaptive noise cancellation to filter out interference from the radiofrequency and magnetic gradient fields in an MRI suite, and demonstrated the ability to detect arrhythmia otherwise obscured during MR scanning. We plan to expand the system to full multiple lead surface and intracardiac electrograms, and to integrate this into a clinical hemodynamic recording system We have used inexpensive parallel computing resources afforded by game-oriented Graphics Processing Units to accelerate reconstruction of computationally-intensive MRI data. We have successfully integrated non-Cartesian parallel imaging in an interactive acquisition and reconstruction setup and demonstrated that real-time reconstruction and visualization is possible for relatively complicated reconstruction algorithms. This will soon be integrated with the scanner software to allow seamless combination with other sequence components. We have developed a system to provide the operator multiple simultaneous representations of real-time MRI data balancing temporal and spatial resolution interactively. The operator chooses the desired representation. We have implemented golden-angle real-time MRI with interactive selection of the temporal resolution. We have developed highly efficient techniques to track complex 3 dimensional curve MRI catheter devices using minimal (highly undersampled projection imaging) data, allowing for seamless incorporation into a real-time MRI visualization system. This allows combination of two- and three-dimensional data in complex catheter interventional procedures. Similarly, we have developed techniques to eliminate motion-related ghosting artifact that appears when accelerated, multi-slice, parallel imaging is used for active devices. We are migrating our highly successful local real-time MRI software environment onto a commercial platform to facilitate translation outside of NIH, and to enhance industry and university collaboration. This has required considerable development to update workhorse real-time MRI pulse sequences to facilitate rapid multi-author or multi-institution prototyping. We also continue to develop new approaches to real-time MRI, or to engineer local noncommercial embodiments of real-time MRI to suit the needs of procedures being developed. For example we are developing real-time interactive flow imaging with spiral trajectories. We have developed a new optimal on-line gradient waveform design for rapid flow-insensitive or flow-sensitive imaging. This required development of new gradient waveform algebra and integrated into functional sequences. We are also working on several pulse-sequence approaches to reduce incident heating of conductive devices during real-time MRI. Finally we are developing custom user-input devices to assist catheter operators more effectively to prescribe desired slice prescriptions without distracting from their primary catheter manipulation procedures.